Question

After reading the information presented in this module and other sources, write a two-page paper that identifies three companies that have been using big data. Explain how big data is helping these companies improve the efficiency of their operations. How could big data privacy risks be eliminated or minimized?

Answer 1

BIG DATA :

• Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately – an effort that’s slower and less efficient with more traditional business intelligence solutions.
• Big data in retail is basic to traget and hold customers, streamline activities, upgrade production network, improve business choice and at last set aside cash.

1- Walmart :

• Walmart relies on big data to get a real-time view of the workflow in the pharmacy, distribution centers and throughout our stores and e-commerce.
• Walmart uses simulations at the pharmacy to find out how many prescriptions are filled in a day & to determine the busiest times during a day or months. This data helps the pharmacy with staff scheduling and to reduce the amount of the time it takes a prescription to be filled.
• With over 20,000 stores in 28 countries, Walmart is the largest retailer in the world. So it’s fitting then that the company is in the process of building the world’s largest private cloud, big enough to cope with 2.5 petabytes of data every hour. To make sense of all this information, Walmart has created what it calls its Data Café – a state-of-the-art analytics hub located within its Bentonville, Arkansas headquarters.
• The Data Café allows huge volumes of internal and external data, including 40 petabytes of recent transactional data, to be rapidly modelled, manipulated and visualised. Speaking to me about the project, senior statistical analyst Naveen Peddamail said, “If you can’t get insights until you’ve analysed your sales for a week or a month, then you’ve lost sales within that time.”

2- True Fit :

• The e-commerce shopping mall is littered with abandoned shopping carts. Consider this: an average of 73.9 percent of carts don’t make it to the check out, according to the most recent data from SaleCycle. While it’s no surprise that the preponderance of discarded baskets are found in the travel industry coming in second is apparel.
• “Only about 10 percent of apparel and footwear purchases happen online,” Romney Evans tells FORBES. The co-founder of TrueFit, a data analytics company, believes sizing plays a big part in consumers’ lack of confidence. Drapers Etail Report found that sizing problems accounted for more than 70% of fashion purchased online was subsequently returned.
• TrueFit is privately held and therefore reluctant to reveal revenue numbers or specifics about its current clients. Adler did say, “We find that 78 percent of all transactions come from people who never purchased online,” a 3-6x lift in conversion rates, and 10-50 percent reduction in returns. “We are getting millions to have a fluid experience.”
• Creating that profile only takes 60 seconds, Adler maintains, another crucial point to keep customers engaged. Between the Pandora-like predictive analytics and the massive amount of data, Adler says TrueFit is poised to disrupt retailing. “If you have trillion market and only 10 percent is online you have to be able to engage people en masse.”
• TrueFit’s personal profiles from shoppers now number in the millions, says Adler, but there’s no need to fear the NSA, or anyone else, scooping up stats on how big your butt is in those jeans. Adler underscores all data from shoppers remains anonymous, even as it learns your preferences from the items you’re buying across different retailers.

3- Amazon :

• 1. Alexa Voice Recordings

  Thanks to virtual assistants such as the Echo and Echo Show, which includes a camera as well as a speaker, getting the weather forecast or ordering more shampoo are a simple voice command away. What customers may not realize, however, is that their audio recordings may be uploaded to Amazon’s servers.

• 2. Ring Video Footage

  Amazon became a major player in the growing home security market when it purchased Ring in 2018. However, the company raised eyebrows among privacy advocates by partnering with hundreds of law enforcement agencies across the country, often supplying surveillance footage from customers without their consent. Many police departments have also developed voluntary camera registries where homeowners can submit footage on their own.

• 3. Personalized Recommendation System

  Amazon is a leader in using a comprehensive, collaborative filtering engine (CFE). It analyzes the items you purchased previously, what is in your online shopping cart or on your wish list, which products you reviewed and rated, and what items you search for most. This information is used to recommend additional products that other customers purchased when buying those same items.

• 4. Book Recommendations From Kindle Highlighting

  After acquiring Goodreads in 2013, Amazon integrated the social networking service of approximately 25 million users into some Kindle functions. As a result, Kindle readers can highlight words and notes and share them with others as a means of discussing a book. Amazon regularly reviews words highlighted in your Kindle to determine what you are interested in learning about. The company may then send you additional e-book recommendations.

• 5. One-Click Ordering

  Because big data shows that you shop elsewhere unless your products are delivered quickly, Amazon created One-Click ordering. One-Click is a patented feature automatically enabled when you place your first order and enter a shipping address and payment method. When choosing One-Click ordering, you have 30 minutes in which you may change your mind about the purchase. After that, the product is automatically charged via your payment method and shipped to your address.

• 6. Anticipatory Shipping Model

  Amazon’s patented anticipatory shipping model also uses big data for predicting the products you are likely to purchase, when you may buy them, and where you might need the products. The items are sent to a local distribution center or warehouse so they will be ready for shipping once you order them. Amazon uses predictive analytics to increase its product sales and profit margins while decreasing its delivery time and overall expenses.